Network Simulation Neighborhood Segmentation
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Solution Overview
Problem
The computational complexity of simulating and optimizing wireless communication networks increases significantly with the number of cells to be evaluated, making large-scale network evaluations computationally expensive and inefficient.
Innovation Solution
Divide the network into neighborhoods, where each neighborhood is represented by a given cell and its relevant neighbor cells, allowing for localized simulations and optimizations, reducing the number of cells to be evaluated and improving computational efficiency by using thresholding techniques based on geographic distance or reverse link interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of cells to be evaluated increases, then the network coverage evaluation becomes more comprehensive, but the simulation runtime increases monotonically and frequently non-linearly
Solution Approach 1:
The patent divides the wireless communication network into multiple neighborhoods, where each neighborhood contains a cell to be evaluated and its relevant neighbor cells. This segmentation allows the network to be evaluated in smaller, manageable portions rather than as a single large system, reducing the computational burden and simulation runtime while maintaining evaluation comprehensiveness through systematic coverage of all cells and their interactions.
2Manufacturing precision
If the number of cells to be evaluated increases, then the network optimization becomes more accurate, but the computational complexity increases significantly
Solution Approach 1:
The patent segments the network evaluation process into neighborhood-based evaluations. Each neighborhood evaluation focuses on a specific cell and its relevant neighbors, reducing the computational complexity from O(N^2) for full network evaluation to O(S) where S is the structural constant representing neighborhood size. This segmentation maintains optimization accuracy by systematically evaluating all cells while reducing overall computational burden.
Solution Approach 2:
The patent applies local quality by evaluating each neighborhood with specific characteristics relevant to that local area rather than applying uniform evaluation across the entire network. Each neighborhood evaluation is tailored to the specific cells and mobiles within that neighborhood, improving computational efficiency while maintaining overall network optimization accuracy through the aggregation of local evaluations.
3Reliability
If independent large-scale network evaluations are performed, then the network design optimization is thorough, but the computational cost becomes increasingly expensive
Solution Approach 1:
The patent performs multiple independent neighborhood evaluations instead of single full network evaluations. Each neighborhood evaluation is computationally inexpensive (O(S) vs O(N^2)), but collectively they provide thorough network design optimization by evaluating all cells and their interactions. This approach maintains reliability and thoroughness while dramatically reducing computational cost and energy consumption.
Data Source
AI summary
In a method of simplifying simulation of a wireless communication network, the network may be divided into one or more neighborhoods. A neighborhood may be represented by a given cell to be evaluated and possibly one or more neighbor cells of the given cell. A desired simulation of one or more of the neighborhoods may be implemented in order to evaluate network performance. The neighborhood may be determined as a function of reverse link interference information, path loss information, or on a geographic distance between cells.